class: left, title-slide .title[ # Introduction<br><font size="5" color="black"> <a href="https://danielw2904.github.io/data-based-storytelling/">Data-based Storytelling</a></font> ] --- # Lost in data Translation ___ .center[ > Hire as many data scientists as you can find - > you’ll still be lost without translators to connect analytics with real business value. > > <footer>- McKinsey and Company</footer> ] --- # Lost in data Translation ___ - [Teaching a computer to tell the difference between a puppy and a kitten](https://colab.research.google.com/github/fastai/fastbook/blob/master/01_intro.ipynb#scrollTo=7qeB_WUKhz86) is neat but... -- .center[ > By 2025 __Chief Data Officers__ and their teams function as a __business unit with profit-and-loss responsibilities__. The unit, in partnership with business teams, is responsible for ideating new ways to use data, __developing a holistic enterprise data strategy (and embedding it as part of a business strategy)__, and incubating new sources of revenue by __monetizing data services and data sharing__. > > <footer>- McKinsey and Company</footer> ] --- # Lost in data Translation ___ .pull-left[ > you’ll [...] be __lost without translators to connect analytics with real business value__. > >By 2025 [data teams will be], __developing a holistic enterprise data strategy (and embedding it as part of a business strategy)__ [...]. > <footer>- McKinsey and Company</footer> ] .pull-right[] --- # Lost in data Translation ___ .pull-left[ Many data applications are: - New: `ChatGPT` - Persuasive (but possibly wrong):  - Complex: > With its 175 billion parameters, its hard to narrow down what GPT-3 does. ([sciencefocus.com](https://www.sciencefocus.com/future-technology/gpt-3/)) ] -- .pull-right[__What is needed__: - __Value__ ] --- .center[  ] --- .center[  ] --- # Goals of this course ___ - Move from _showing data_ to __telling stories with data__ (Knaflic, 2015) -- .pull-left[ <img src="data:image/png;base64,#01-Introduction_files/figure-html/example-covid-1.png" width="100%" /> ] -- .pull-right[ <img src="data:image/png;base64,#01-Introduction_files/figure-html/plot_hl-1.png" width="100%" /> ] --- count: false # Goals of this course ___ - Move from _showing data_ to __telling stories with data__ (Knaflic, 2015) <img src="data:image/png;base64,#01-Introduction_files/figure-html/plot_out-1.png" width="50%" /> --- count: false # Goals of this course ___ - Move from _showing data_ to __telling stories with data__ (Knaflic, 2015) - Translate raw data to actionable business cases - Go beyond statistical jargon to explain real world phenomena --- count: false # Goals of this course ___ - Move from _showing data_ to __telling stories with data__ (Knaflic, 2015) - Translate raw data to actionable business cases - Go beyond statistical jargon to explain real world phenomena ### What we need - Theoretical knowledge on storytelling and data-visualization - Tools to present data: `R` with packages like `ggplot2`, `gt`, and `flextable` --- # Why R? ___ - Extremely flexible -- - e.g., animations .center[  ] --- count: false # Why R? ___ - Extremely flexible - `\(~19.000\)` available packages ranging from - [visualization](https://ggplot2.tidyverse.org) to - [all](https://www.stat.berkeley.edu/~breiman/RandomForests/) [types](https://www.tidymodels.org) [of](https://google.github.io/CausalImpact/CausalImpact.html) [statistical](https://cran.r-project.org/web/views/Econometrics.html) [analyses](https://facebook.github.io/prophet/), - [web-scraping](https://rvest.tidyverse.org), or - ["data wrangling"](https://dplyr.tidyverse.org). - Well documented and widely used --- # Story time ___ .vertical-center[**Does someone know a story?**] --- count: false # Story time ___ .center[ <iframe width="737" height="415" src="https://www.youtube-nocookie.com/embed/xV9HnITo2C0" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> ] --- # Three-act structure ___ .pull-left[ .dense[ 1. Setup - _Why should I pay attention?_ - Introduce __protagonist__ ] ] .pull-right[ <img src="data:image/png;base64,#Graphics/story_setup.png" height="30%" /> ] --- count: false # Three-act structure ___ .pull-left[ .dense[ 1. Setup - _Why should I pay attention?_ - Introduce protagonist - Present the __problem__ ] ] .pull-right[ <img src="data:image/png;base64,#Graphics/setup_problem.png" height="30%" /> ] --- count: false # Three-act structure ___ .pull-left[ .dense[ 1. Setup - _Why should I pay attention?_ - Introduce protagonist - Present the problem - Call to __action__ ] ] .pull-right[ <img src="data:image/png;base64,#Graphics/setup_call.png" height="30%" /> ] --- count: false # Three-act structure ___ .pull-left[ .dense[ 1. Setup - _Why should I pay attention?_ - Introduce protagonist - Present the problem - Call to action 2. Confrontation - _Why should I endorse?_ - __Attempts__ to resolve the problem ] ] .pull-right[ <img src="data:image/png;base64,#Graphics/atempt.png" height="15%" /> ] --- count: false # Three-act structure ___ .pull-left[ .dense[ 1. Setup - _Why should I pay attention?_ - Introduce protagonist - Present the problem - Call to action 2. Confrontation - _Why should I endorse?_ - Attempts to resolve the problem - "What has been done?" * Build the problem / show __imbalance__ * Get __credibility__ ] ] .pull-right[ <img src="data:image/png;base64,#Graphics/atempt2.png" height="15%" /> ] --- count: false # Three-act structure ___ .pull-left[ .dense[ 1. Setup - _Why should I pay attention?_ - Introduce protagonist - Present the problem - Call to action 2. Confrontation - _Why should I endorse?_ - Attempts to resolve the problem - "What has been done?" - Make clear why _your_ solution is needed and the __audience can drive action__ ] ] .pull-right[ <img src="data:image/png;base64,#Graphics/failed.png" height="15%" /> ] --- count: false # Three-act structure ___ .pull-left[ .dense[ 1. Setup - _Why should I pay attention?_ - Introduce protagonist - Present the problem - Call to action 2. Confrontation - _Why should I endorse?_ - Attempts to resolve the problem - "What has been done?" - Make clear why _your_ solution is needed and the audience can drive action 3. Resolution - _What can I do?_ - Present your __solution__ - Call to action ] ] .pull-right[ <img src="data:image/png;base64,#Graphics/success.png" height="15%" /> ] --- count: false # Three-act structure ___ .pull-left[ .dense[ 1. Setup - _Why should I pay attention?_ - Introduce protagonist - Present the problem - **Call to action** 2. Confrontation - _Why should I endorse?_ - Attempts to resolve the problem - "What has been done?" - Make clear why _your_ solution is needed and the __audience can drive action__ 3. Resolution - _What can I do?_ - Present your solution - **Call to action** ] ] .pull-right[ <img src="data:image/png;base64,#Graphics/success.png" height="15%" /> ] ??? - When to call for action depends on audience - How knowledgeable? - Relationship? Establish credibility? --- # SUCCESS! ___ .center[ <img src="data:image/png;base64,#Graphics/yaaay.png" width="50%" /> ] --- # Here's to the crazy ones! ___ .center[ <iframe width="737" height="415" src="https://www.youtube-nocookie.com/embed/YBJAvi3A0H8" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> ] --- class: dense logo-small hide-footer hide-logos-bottom __Setup__ - Introduce "the crazy ones": Einstein, Dylan, MLK, Earhart... - "See things differently", "not fond of rules", "no respect for the status quo" -- __Confrontation__ - "You can quote them, disagree with them, glorify, or vilify them" -- - You should buy-in because: "the only thing you can't do is ignore them" -- - "While some may see them as the crazy ones..." -- __Resolution__ - "We see genius." - "Because the people who are crazy enough to think they can change the world, are the ones who do." ??? This establishes two groups: - Those who see them as the crazy ones `\(\Rightarrow\)` boring - Those who see genius `\(\Rightarrow\)` cool __Which group are you in?__ --- class: hide-footer hide-logo-bottom hide-logo background-color: #0F0F0F .center[ <img src="data:image/png;base64,#Graphics/Think_Different.svg" height="100%" /> ] -- .center[<font color="white">Call to action</font>] --- # Some recommendations ___ - Have a 1 min. elevator-pitch ready - Don't be afraid to cut material out - What is relevant to the audience? -- - In school: success is presenting knowledge both you and the teacher have -- - In Life: success is presenting knowledge the audience wants to have --- class: logo-small hide-footer # Data Visualization ___ .pull-largeleft[ - Starting with Cleveland and McGill (1984) researchers have explored which types of graphs can be read accurately by humans ] .pull-smallright[ <div class="figure"> <img src="data:image/png;base64,#Graphics/visual_accuracy.jpeg" alt="&lt;a href=&quot;https://www.gabrielaplucinska.com/blog/2017/8/7/pie-charts&quot;&gt;source&lt;/a&gt;" width="70%" /> <p class="caption"><a href="https://www.gabrielaplucinska.com/blog/2017/8/7/pie-charts">source</a></p> </div> ] --- ## Share of population vaccinated ___  --- ## Share of population vaccinated ___ <!-- --> ??? 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Starting with Cleveland and McGill (1984) researchers have explored which types of graphs can be read accurately by humans - However, accuracy is not always the (only) goal for data story telling - Graphs need to be engaging! ] .pull-smallright[ <div class="figure"> <img src="data:image/png;base64,#Graphics/visual_accuracy.jpeg" alt="&lt;a href=&quot;https://www.gabrielaplucinska.com/blog/2017/8/7/pie-charts&quot;&gt;source&lt;/a&gt;" width="70%" /> <p class="caption"><a href="https://www.gabrielaplucinska.com/blog/2017/8/7/pie-charts">source</a></p> </div> ] --- class: hide-footer ## Focus: preattentive attributes ___ .center[ <div class="figure"> <img src="data:image/png;base64,#Graphics/preattent.png" alt="&lt;a href=&quot;http://www.perceptualedge.com/articles/ie/visual_perception.pdf&quot;&gt;source&lt;/a&gt;" width="55%" /> <p class="caption"><a href="http://www.perceptualedge.com/articles/ie/visual_perception.pdf">source</a></p> </div> ] --- ## Focus: preattentive attributes ___ <!-- --> .pull-left[<iframe src="https://beepmyclock.com/widget/stopwatch" frameborder="0" style="border:0;height:100px;-moz-transform: scale(0.5, 0.5); -webkit-transform: scale(0.5, 0.5); -o-transform: scale(0.5, 0.5); -ms-transform: scale(0.5, 0.5); transform: scale(0.5, 0.5); -moz-transform-origin: top left; -webkit-transform-origin: top left; -o-transform-origin: top left; -ms-transform-origin: top left; transform-origin: top left;" ></iframe>] .pull-right[Adapted from Knaflic (2015)] --- ## Focus: preattentive attributes ___ <!-- --> .pull-left[<iframe src="https://beepmyclock.com/widget/stopwatch" frameborder="0" style="border:0;height:100px;-moz-transform: scale(0.5, 0.5); -webkit-transform: scale(0.5, 0.5); -o-transform: scale(0.5, 0.5); -ms-transform: scale(0.5, 0.5); transform: scale(0.5, 0.5); -moz-transform-origin: top left; -webkit-transform-origin: top left; -o-transform-origin: top left; -ms-transform-origin: top left; transform-origin: top left;" ></iframe>] .pull-right[Adapted from Knaflic (2015)] --- ## Focus: preattentive attributes ___ <!-- --> --- # Getting started with R ___ .center[ <iframe width="737" height="415" src="https://www.youtube.com/embed/SAxhoYIt7pk" title="Getting started with R" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> ] --- # Go to [getting_started.html](./getting_started.html) - [Palmer Penguins](https://allisonhorst.github.io/palmerpenguins/index.html#meet-the-palmer-penguins) --- # References ___ .scrollable[ ### Papers & Books Cleveland, W. S. and R. McGill (1984). "Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods". In: _Journal of the American Statistical Association_ 79.387, pp. 531-554. ISSN: 01621459. URL: [http://www.jstor.org/stable/2288400](http://www.jstor.org/stable/2288400). Guidotti, E. and D. Ardia (2020). "COVID-19 Data Hub". In: _Journal of Open Source Software_ 5.51, p. 2376. DOI: [10.21105/joss.02376](https://doi.org/10.21105%2Fjoss.02376). Knaflic, C. (2015). _Storytelling with Data: A Data Visualization Guide for Business Professionals_. Wiley. ISBN: 9781119002253. Schwabish, J. (2021). _Better data visualizations: A guide for scholars, researchers, and Wonks_. Columbia University Press. ### Links [Five Fifty: Lost in translation](https://www.mckinsey.com/business-functions/people-and-organizational-performance/our-insights/five-fifty-lost-in-translation#) [LEADERSHIP LAB: The Craft of Writing Effectively](https://www.youtube.com/watch?v=vtIzMaLkCaM) [The age of analytics: Competing in a data-driven world](https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-age-of-analytics-competing-in-a-data-driven-world) [The data-driven enterprise of 2025](https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-data-driven-enterprise-of-2025) [Think Different Logo](https://de.wikipedia.org/wiki/Think_Different#/media/Datei:Apple_logo_Think_Different_vectorized.svg) [Preattentive attributes](http://www.perceptualedge.com/articles/ie/visual_perception.pdf) ]